1st EBRAINS Student Conference on Interdisciplinary Brain Research

Student

Early Bird (until 22 January 2026): 110 €
Regular (after 22 January until 25 February): 160 €

Regular

Early Bird (until 22 January 2026): 160 €
Regular (after 22 January until 25 February): 220 €

Registration will open in September 2025!

Please note: this is an on-site conference. Virtual attendance is not available.

What is included in the registration fee?

 Registration to the conference includes:

• Admission to all scientific sessions
• Admission to all workshops
• Admission to welcome reception
• Conference material
• Coffee & lunch during the conference 

Please note: the registration fee does not include travel or accommodation.

Payment methods

Payments can be made in Euros (€) using the following methods:

• Credit or debit card
• PayPal
• Sofort
• SEPA Direct Debit

Fee Waiver Application Guidelines

A limited number of registration fee waivers are available to support participants whose abstracts have been accepted for presentation at the EBRAINS Student Conference on Interdisciplinary Brain Research.

The application period opens on 1 December and closes 6 January 2026.

Participants with an accepted abstract and demonstrated financial need may apply for a registration fee waiver covering the full conference registration fee.
Applicants may apply for a fee waiver only (no travel funding is available through this call). Individuals who have previously received a travel grant are still eligible to apply, provided they meet the remaining eligibility criteria.

Priority Considerations

In line with our commitment to diversity and inclusion, priority will be given to:

•    Applicants from low- and middle-income countries
•    Individuals from underrepresented gender groups
•    Applicants from underrepresented regions
•    Master’s students, PhD students, or medical students (clinical).

Eligibility Criteria

To apply, applicants must:

•    Have an accepted abstract (oral or poster presentation)
•    Be Master’s students, PhD students in neuroscience, early-career postdoctoral researchers (within five years of commencing their postdoctoral position), or medical students (clinical) actively engaged in neuroscience-related research.

How to Apply

To apply for a registration fee waiver, please complete the application form and upload one PDF file containing the following documents:

1.    Short CV (maximum 2 pages)
2.    Statement of Financial Need (up to 150 words)
Briefly explain why you are requesting a fee waiver.
3.    Abstract Acceptance Confirmation
A copy of the official email from the EBRAINS Education Team confirming your abstract acceptance.
4.    (Optional but recommended) Letter of Support from Supervisor (max. 1 page)

This is particularly helpful for Master’s and PhD students.

Timeline

•    Applications open: 1 December 2026
•    Application deadline: 6 January 2026
•    Notification of results: by 20 January 2026 (at the latest)

• 12:30 - 13:30 - Registration + Welcome Coffee
• 13:30 - 14:30 - Welcome and Introduction
• 14:00 - 15:00 - Keynote I Topic: Hannah Monyer - Clinical Neurobiology
• 15:00 - 16:00 - Student Session I Topic:
• 16:00 - 16:30 - Coffee break
• 16:30 - 17:30 - Keynote II Topic: Sabine Liebscher - Neurodegeneration / Neuropathology
• 17:30 - 19:00 - Poster Session I
• 19:30 - 22:30 - Networking Session Welcome Reception

• 8:00 - 9:00 - Registration
• 9:00 - 11:30
  • Workshop I - Arbor
  • Workshop II - Neuromorphic computing / BrainScaleS
  • Workshop III - The Virtual Brain
• 11:30 -12:00 - Coffee break
• 12:00 - 13:00 - Student Session II Topic:
• 13:00 - 14:00 - Lunch break
• 14:00 - 15:00 - Keynote III Topic: Sergii Tukaiev-Cognitive and Affective Neuroscience
• 15:00 - 16:00 - Student Session III
• 16:00 - 16:30 - Coffee break
• 16:30 - 17:30 - Keynote IV Topic: Barbora Rehák-Bučková - Neuroimaging Analysis / Neuroinformatics
• 17:30 - 19:00 - Poster Session II

• 8:00 - 9:00 - Registration
• 9:00 - 11:30
  • Workshop IV - NEST
  • Workshop V - Equality, Equity, Diversity, Inclusion (EEDI): How to collaborate with almost everyone   
  • Workshop VI - Brain Atlas
• 11:30 -12:00 - Coffee break
• 12:00 - 13:00 - Keynote V Topic: Sandra Diaz Applied & Computational Neuroscience
• 13:00 - 14:00 - Lunch break
• 14:00 - 15:00 - Student Session IV Topic:
• 15:00 - 16:00 - AMA Session - Karin Grasenick
• 16:00 - 16:30 - Coffee break
• 16:30 - 17:30 - Plenary Discussion?
• 17:30 - 18:00 - Awards & Closing
• 18:00 - 22:00 - Optional Event: Evening Social at the Pub

Information coming soon.

BrainScaleS-2 is a mixed-signal neuromorphic system that emulates synapse and neuron dynamics in analog circuits, while digital logic manages event communication and system configuration. Its design enables the emulation of neural networks at speeds which are around 1000 times faster than biological real time. This acceleration is particularly valuable for neuroscientific experiments requiring long time scales, extensive parameter searches, or the exploration of spiking neural networks.

In this tutorial, we will introduce the BrainScaleS-2 system and guide participants through interactive exercises using Jupyter notebooks. Attendees will gain hands-on experience programming and exploring the hardware live via the EBRAINS infrastructure.

Target group

• Researchers interested in using neuromorphic hardware alongside simulations
• Students and scientists curious about analog neuromorphic systems

Expected learning outcomes

• The fundamentals of the BrainScaleS-2 system and analog neuromorphic hardware
• How to run experiments on BrainScaleS-2 via the EBRAINS compute infrastructure
• How to define experiments using PyNN or PyTorch for BrainScaleS-2

Workshop speakers

Jakob Kaiser | Institute of Computer Engineering (ZITI), Heidelberg University, Germany  

Jakob Kaiser studied physics at Heidelberg University. He did his bachelor thesis in the field of condensed matter physics before switching to neuromorphic hardware for his masters thesis. Currently he is pursuing a PhD in the Electronic Visions group which develops the BrainScaleS-2 system. He explores multi-compartmental neuron models and investigates simulation-based inference as a tool to parameterize experiments on neuromorphic hardware.

Amani Atoui| Institute of Computer Engineering (ZITI), Heidelberg University, Germany  /

Amani Atoui did her bachelor in electrical and computer engineering, and her master’s in computational neuroscience. She found her research interests in studying synaptic plasticity using analog neuromorphic hardware at the Electronic Visions group at Heidelberg University. She first joined the group for her master’s thesis, and is now pursuing her PhD where she explores the advantages of running plasticity experiments on BrainScaleS-2.

Abstract 

Take a guided tour through The Virtual Brain (TVB) ecosystem and discover how real patient data can be transformed into a personalized digital twin. Learn how to simulate brain dynamics and perform model fitting, leveraging the multiple entry points of the EBRAINS platform and advanced HPC techniques. 

The workshop is structured in two parts: 

• Conceptual Overview  
• An introduction to TVB’s ecosystem with a focus on architecture, data pipelines, and modeling capabilities.
• Hands-On Exploration 
• Participants will engage with TVB’s interfaces (GUI, widgets, scripting tools, or APIs) on EBRAINS to run simulations, perform model fitting, inspect results and explore practical workflows.
• Participants will launch an HPC–GPU scalable pipeline for fitting TVB biophysical models — specifically the Jansen–Rit and Larter–Breakspear models — to EEG data, making use of complexity, criticality and functional connectivity as fitting metrics, via EBRAINS at the Jülich Supercomputer Centre. 

No prior experience with TVB is required — just curiosity about how computational neuroscience is shaping the future of precision medicine. 

Target group  

• Neuroscience and computer science background are useful but not required
• Basic familiarity with Python, Jupyter Notebook, CPU/GPUs is beneficial but not required 

Expected learning outcomes  

• Road from real patient to digital brain. 
• Learn how to simulate with TVB. 
• Introduction to advanced HPC usage for fitting. 
• Discover different entry points of the EBRAINS platform for simulation and fitting.   

Workshop speakers

Paula Prodan |Codemart, Romania

Teodora Misan | Codemart, Romania

Michiel Van Der Vlag | Forschungszentrum Jülich, Germany

Information coming soon.

Abstract

This workshop offers inter- and transdisciplinary methods and tools for collaborative work on projects that can also be especially beneficial for virtual collaborations:  

• The integration of various disciplines, thinking patterns, experiences and work styles.
• Procedures and Tools for appreciative collaboration in heterogenous teams.
• Fair work distribution, virtual decision-making and conflict resolution.  

Methods 

Trigger Talks on interdisciplinary collaboration, challenges and tools; group work; case studies; individual and group reflection.  

Expected Learning Outcomes

• Recognising collaborative challenges routed in the interplay of different disciplines, locations, career aspirations and cultures.
• Knowing tools that support a productive international research collaboration
• First practical experiences with applying these tools  

Target audience

Everyone interested in effective international research collaborations.  

Workshop Speakers

Timo Dickscheid | Forschungszentrum Jülich, Germany

Kimberley Lothmann | Forschungszentrum Jülich, Germany

More information coming soon.

Keynote I: How do inhibitory neurones control neuronal networks locally and at long distance: implications in health and disease 

The generation of episodic memories, that is of memories related to “what” happens “where” and “when”, depends on the intact function of the hippocampal formation. Over the past two decades, we focused on the study of a particular class of neurones, namely the inhibitory GABAergic interneurones, that control the timing of neuronal activity within neuronal networks. They can we viewed as the “directors” of an orchestra: it is the other neurones that make the music, they are the “players”, but the GABAergic interneurones control when the members of the orchestra set in to play. Thus, it is not surprising that malfunction of GABAergic interneurones results in serious impairments in the entire network which translates into deficits at the behavioural level. In the hippocampal formation, reduced recruitment of GABAergic interneurones is associated with impairments of spatial coding and spatial memory. 

Until recently, the dogma held that in the cortex all GABAergic cells are “interneurones”, that is their axons are confined to the local network and hence their control is restricted to the brain area their cell bodies are located in. However, with the advent of viral tracing techniques, my lab discovered that a minority of GABAergic cells are not “interneurones” but “projection neurones”. Most interestingly, they project at long distance and control in the target areas specifically GABAergic interneurones, that is the “local orchestra directors”. Thus, GABAergic projection neurones can be considered “master cells” as they govern the activity in multiple networks. We have reason to believe that their metabolic activity is high accounting for enhanced vulnerability in certain neurodegenerative diseases. I will discuss how we study these neurones at the cellular, network and behavioural level.

Sabine Liebscher is a physician and neuroscientist, currently Professor of Systems Neurobiology and Director of the Institute of Systems Neuroscience at the Medical University of Innsbruck, a position she has held since February 2025. Before her appointment in Innsbruck, she served as W2 Professor of Cellular Neurophysiology at the Faculty of Medicine, University of Cologne, and previously led a Clinician Scientist research group while training in Neurology at the Institute of Clinical Neuroimmunology, at the University hospital Munich of the Ludwig Maximilians University (LMU) Munich, Germany. 

She studied medicine at the Technical University of Dresden, where she also completed her MD thesis. In 2007, she joined the laboratory of Nobel Laureate Paul Greengard at The Rockefeller University in New York. She later earned her PhD in Neuroscience with distinction from the Max Planck Institute of Neurobiology and the LMU Munich. 

In 2014, she established her independent junior research group through the prestigious Emmy Noether Programme of the German Research Foundation (DFG). Her research focuses on the pathophysiology of neurodegenerative diseases, particularly amyotrophic lateral sclerosis (ALS). She investigates how neural circuits and their components contribute to disease symptoms and drive the degenerative process. Her work integrates clinical insight with experimental neuroscience, combining in vivo two-photon imaging, single-cell transcriptomics, and viral circuit manipulation to uncover network-level mechanisms of neurodegeneration. 

Keynote Lecture II: Hidden Failure: Circuit Dysfunction Beyond Cell Loss in Neurodegeneration 

Neurodegenerative diseases are increasingly recognized as disorders of neural circuits rather than isolated cell death. Functional alterations in defined neuronal populations and networks often arise before overt degeneration and persist beyond it. Our work focuses on identifying such circuit-level dysfunctions to uncover early pathogenic mechanisms and new therapeutic targets. 

I will present examples from amyotrophic lateral sclerosis (ALS), the most common adult-onset motor neuron disease characterized by the loss of upper and lower motor neurons. Our studies reveal persistent cortical hyperexcitability is linked to hyperresponsive pyramidal neurons in cortical layer 2/3, which provide excess glutamatergic input to upper motor neurons. We further demonstrate that noradrenergic input to the motor cortex is markedly reduced in both mouse models and ALS patients. These alterations arise before overt neuronal loss and contribute to abnormal motor output, suggesting that network dysfunction, not simply degeneration, underlies selective vulnerability. Targeting compromised circuit elements delays disease onset and progression, underscoring their pathophysiological importance. 

Parallel investigations in spinocerebellar ataxia (SCA), a degenerative disorder characterized by Purkinje neuron death, also reveal profound circuit-level disruption within the cerebellar cortex. We identified hyperactive molecular layer interneurons that exert excessive inhibition onto Purkinje cells, driving their synaptic degeneration and loss. Chemogenetic suppression of these interneurons alleviates motor symptoms within minutes and extends survival in transgenic mice. 

Together, these findings point to a convergent principle: defined circuit elements undergo persistent activity changes that trigger functional disconnection and network failure. By dissecting these mechanisms at the level of identified cell types and synaptic interactions, our work lays the groundwork for therapeutic strategies that target circuit dysfunction rather than rely solely on cell replacement.

Sergii Ukaiev is involved in the study of the mechanisms of stress, including the establishment of specific biomarkers of mental and stress-related disorders, the impact of stress on cognitive processes, and the effectiveness of stress-coping methods. With more than 30 years of conducting neuroscience research across various departments and using an interdisciplinary approach, he evaluates complex problems from new perspectives, integrating insights from both the mind and the brain. His accumulated knowledge and experience are being applied to the development of a Neuro-Assistive Robotic Intellectual System and non-invasive interfaces designed to counteract stress-related disorders, restore brain functions, and improve cognitive performance. He has also served as a section editor for Stress & Health.

Keynote III: Neurophysiology of emotional burnout. Biomarkers 

Burnout syndrome is one of the forms of chronic occupational stress, and develops gradually, often goes unnoticed, with symptoms that may take years to manifest and lead to significant mental and behavioral changes. There is no single view on the nature and structure of emotional burnout. Boyko's psychological construct of Emotional Burnout (EB) defines Syndrome as a mechanism of psychological defence in the form of complete or partial excluding of emotions in response to traumatic influences and includes three key stages: Anxiety Tension, Resistance, and Exhaustion. Despite its impact, the processes underlying burnout remain largely unknown due to a lack of specialized studies identifying specific biomarkers. Early detection of burnout, particularly at the critical onset of symptoms, is essential. 

752 volunteers aged 18 to 26 years participated in this study. To establish EEG correlates of emotional burnout during rest state we used special software written in Python 3.6 to implement Power Spectral Density calculation, the interhemispheric and intrahemispheric average coherence and Detrended Fluctuation Analysis (DFA). 

Values of normalized power spectral densities (PSD), DFA exponent, and average coherence suggest the formation of Anxiety Tension stage impacts primarily processes related to short-term memory and focused attention. The Exhaustion formation is accompanied by changes in visual and verbal processing, as well as emotional processes (such as discretion and analysis). 

The obtained data on neural characteristics in burnout-ed subjects may help to understand the mechanisms of decline in cognitive function and emotion regulation and to search for adequate methods of treatment. 

Barbora Rehák-Buckova is a postdoctoral researcher at the Donders Institute, where she focuses on normative modelling of cognitive scales across heterogeneous cohorts to improve prediction of schizophrenia outcomes. Her work draws on her background in artificial intelligence, statistics, and computational biology. She completed her Ph.D. at the Czech Technical University in Prague, where she developed methods for multi-modal neuroimaging data analysis. Throughout her career, she has contributed to national health initiatives in the Czech Republic and has been grateful for the support from grants such as the Fulbright Fellowship at the University of Pennsylvania. 

Keynote IV: The promises and pitfalls of normative modelling in precision medicine 

Normative modelling is a method that has become widely popular in neuroscience over the past decade. Owing to the ever-growing availability of neuroimaging data, the promise to parse heterogeneity and personalise inferences has become much more tangible. However, where is the field now and what should be our steps moving forward? In this talk, I will touch upon the most popular methods used for constructing cross-sectional normative models across neuroimaging modalities, their applications, limitations, and the types of inferences that should and should not be made. Furthermore, I will discuss the longitudinal aspect of normative modelling and the emerging methods for making longitudinal inferences. Yet understanding brain trajectories alone does not solve the core challenge: predicting and understanding behavioural outcomes. I will address the limitations of brain-behaviour analyses and explain why focusing on modelling the brain is not enough when our measurements of behaviour are unreliable and variable. Can normative modelling offer solutions here as well? 

Sandra Diaz Pier was born in Mexico where she obtained a bachelor in electronic systems engineering and a masters in computer science. She also worked in industry as quality assurance leader and as software developer for several years. In 2011 she moved to Ontario, Canada to get a second masters in electrical engineering. In 2014 she moved to Germany to work as graduate researcher at the Simulation and Data Lab Neuroscience (SDLN) at the Jülich Supercomputing Centre at Forschungszentrum Jülich, Germany. At the SDLN, she started working at the interface between neuroscience and high performance computing doing methodological research and providing support to domain scientists. At the same time she did her PhD in computer science which she completed in 2021. In 2023 Sandra Diaz was appointed as scientific leader of the SDLN. Her research focus is on high performance computing, simulation of brain dynamics and plasticity at different scales, and optimization. She has participated in several EU projects including the Human Brain Project (HBP), Virtual Brain Cloud, eBrain Health, EBRAINS 2.0 and Virtual Brain Twin. She is an active collaborator in the technical development and education programme of the EBRAINS research infrastructure. She is contributor to open source codes like the NEST simulator (https://github.com/nest/nest-simulator), The Virtual Brain (https://github.com/the-virtual-brain), and L2L (https://github.com/Meta-optimization/L2L).

Keynote V: Using high performance computing to optimize brain models across scales

Scientists use mathematical models to study the brain at  at different spatial and temporal scales, from the molecular level to the whole brain, from ion channel dynamics to cognitive function. These mathematical models are usually highly under-constrained and optimization their parameters is required to make them fit experimental observations and produce useful insight. In this talk I will present a set of scientific use cases where we have used scalable methods on high performance computing systems to optimize models in neuroscience research. The use cases include models from single cells, neural networks and whole brain models as well as spiking neural networks embedded in simulated agents. I will show how supercomputing can be used to accelerate parameter explorations and model optimization, promoting a more rigurous parametrization of models by understanding their statistical variability.

Conference Chairs:

• João Miguel Alves Ferreira | University of Coimbra
• Sinovia Fotiadou | Forschungszentrum Jülich 

Programme Committee:

• João Miguel Alves Ferreira | University of Coimbra
• Arturo Cabrera-Vazquez | Centre Inria de l'Université Grenoble Alpes
• Gabriele Casagrande | Aix-Marseille University
• Sourin Chatterjee | Aix-Marseille University
• Alexey Chervonyy | Heinrich-Heine-Universität Düsseldorf
• Cassandra Dumas | Paris Brain Institute - ICM
• Nataliia Fedorchenko | Forschungszentrum Jülich
• Sinovia Fotiadou | Forschungszentrum Jülich
• Daniela Janeva | Aix-Marseille University
• Carmen Lupascu | National Research Council
• Hannah Mohr | Forschungszentrum Jülich
• Margherita Premi | Politecnico di Milano
• Giacomo Preti | Aix-Marseille University
• Gregorio Rebecchi | Université Côte d’Azur
• Alisha Reinhardt | Heinrich-Heine-Universität Düsseldorf
• Eva Vytvarová | CEITEC - Applied Neuroscience Group
• Alper Yegenoglu | University of Paderborn
• Ekaterina Zossimova | Forschungszentrum Jülich 

Local Host:

• Patrica Reynaud-Bouret | Université Côte d'Azur
• Ingrid Bethus | Université Côte d'Azur
• Chloé Bourgeois | Université Côte d'Azur